Distributed computation and storage have been widely used for processing of big data sets. For many big data problems, with the size of data growing rapidly, the distribution of computing tasks and ...

Arm’s Mohamed Awad, senior vice president and general manager for data center infrastructure, said in March that at the end ...

As someone who has spent the better part of two decades optimizing distributed systems—from early MapReduce clusters to ...

AI workloads are testing traditional centralized systems beyond their limits. Incentivizing distributed energy and data is the answer, says Greg Osuri, CEO of Akash Network.

Objectives Cardiovascular (CV) diseases are associated with adverse outcomes. However, attention has typically focused on ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

SolarBank Corporation (Cboe CA: SUNN) (NASDAQ: SUUN) ("SolarBank" or the "Company"), a leading North American developer, owner, and operator of solar and battery energy storage systems (BESS), is ...

In large-scale parallel computing systems, machines and the network suffer from non-negligible faults, often leading to system crashes. The traditional method to increase reliability is to restart the ...

Kratos Multiphysics (A.K.A Kratos) is a framework for building parallel multi-disciplinary simulation software. Modularity, extensibility and HPC are the main objectives. Kratos has BSD license and is ...

Machines operate autonomously, self-correcting in real time to prevent downtime. Workers, empowered by AI, focus on innovation rather than routine tasks.

Computing 'A first in applied physics': Breakthrough quantum computer could consume 2,000 times less power than a supercomputer and solve problems 200 times faster ...